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#MIT Schwarzman College of Computing

  • How to build AI scaling laws for efficient LLM training and budget maximization

    18 Sep
  • Machine-learning tool gives doctors a more detailed 3D picture of fetal health

    18 Sep
  • DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

    18 Sep
  • A greener way to 3D print stronger stuff

    18 Sep
  • A new generative AI approach to predicting chemical reactions

    18 Sep
  • 3 Questions: The pros and cons of synthetic data in AI

    18 Sep
  • 3 Questions: On biology and medicine’s “data revolution”

    18 Sep
  • MIT researchers develop AI tool to improve flu vaccine strain selection

    18 Sep
  • Simpler models can outperform deep learning at climate prediction

    18 Sep
  • Can large language models figure out the real world?

    18 Sep
  • A new way to test how well AI systems classify text

    18 Sep
  • Eco-driving measures could significantly reduce vehicle emissions

    18 Sep
  • MIT tool visualizes and edits “physically impossible” objects

    18 Sep
  • New algorithms enable efficient machine learning with symmetric data

    18 Sep
  • Robot, know thyself: New vision-based system teaches machines to understand their bodies

    18 Sep
  • A new way to edit or generate images

    18 Sep
  • The unique, mathematical shortcuts language models use to predict dynamic scenarios

    18 Sep
  • Can AI really code? Study maps the roadblocks to autonomous software engineering

    18 Sep
  • How to more efficiently study complex treatment interactions

    18 Sep
  • Changing the conversation in health care

    18 Sep
  • AI shapes autonomous underwater “gliders”

    18 Sep
  • Study could lead to LLMs that are better at complex reasoning

    18 Sep
  • Using generative AI to help robots jump higher and land safely

    18 Sep
  • LLMs factor in unrelated information when recommending medical treatments

    18 Sep
  • Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

    18 Sep
  • A sounding board for strengthening the student experience

    18 Sep
  • Unpacking the bias of large language models

    18 Sep
  • Bringing meaning into technology deployment

    18 Sep
  • Photonic processor could streamline 6G wireless signal processing

    18 Sep
  • Inroads to personalized AI trip planning

    18 Sep
  • Melding data, systems, and society

    18 Sep
  • AI-enabled control system helps autonomous drones stay on target in uncertain environments

    18 Sep
  • Envisioning a future where health care tech leaves some behind

    18 Sep
  • Teaching AI models what they don’t know

    18 Sep
  • Teaching AI models the broad strokes to sketch more like humans do

    18 Sep
  • An anomaly detection framework anyone can use

    18 Sep
  • Building networks of data science talent

    18 Sep
  • AI learns how vision and sound are connected, without human intervention

    18 Sep
  • Learning how to predict rare kinds of failures

    18 Sep
  • The sweet taste of a new idea

    18 Sep
  • With AI, researchers predict the location of virtually any protein within a human cell

    18 Sep
  • Study shows vision-language models can’t handle queries with negation words

    18 Sep
  • MIT Department of Economics to launch James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work

    18 Sep
  • Hybrid AI model crafts smooth, high-quality videos in seconds

    18 Sep
  • New tool evaluates progress in reinforcement learning

    18 Sep
  • Novel AI model inspired by neural dynamics from the brain

    18 Sep
  • Making AI models more trustworthy for high-stakes settings

    18 Sep
  • The MIT-Portugal Program enters Phase 4

    18 Sep
  • Merging design and computer science in creative ways

    18 Sep
  • Designing a new way to optimize complex coordinated systems

    18 Sep
  • “Periodic table of machine learning” could fuel AI discovery

    18 Sep
  • 3D modeling you can feel

    18 Sep
  • MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale

    18 Sep
  • Making AI-generated code more accurate in any language

    18 Sep
  • A faster way to solve complex planning problems

    18 Sep
  • Training LLMs to self-detoxify their language

    18 Sep
  • New method efficiently safeguards sensitive AI training data

    18 Sep
  • Could LLMs help design our next medicines and materials?

    18 Sep
  • New method assesses and improves the reliability of radiologists’ diagnostic reports

    18 Sep
  • Researchers teach LLMs to solve complex planning challenges

    18 Sep
  • For this computer scientist, MIT Open Learning was the start of a life-changing journey

    18 Sep
  • MIT Maritime Consortium sets sail

    18 Sep
  • AI tool generates high-quality images faster than state-of-the-art approaches

    18 Sep
  • Robotic helper making mistakes? Just nudge it in the right direction

    18 Sep
  • Markus Buehler receives 2025 Washington Award

    18 Sep
  • Like human brains, large language models reason about diverse data in a general way

    18 Sep
  • AI model deciphers the code in proteins that tells them where to go

    18 Sep
  • Gift from Sebastian Man ’79, SM ’80 supports MIT Stephen A. Schwarzman College of Computing building

    18 Sep
  • Bridging philosophy and AI to explore computing ethics

    18 Sep
  • Can deep learning transform heart failure prevention?

    18 Sep
  • Creating a common language

    18 Sep
  • Validation technique could help scientists make more accurate forecasts

    18 Sep
  • Aligning AI with human values

    18 Sep
  • Introducing the MIT Generative AI Impact Consortium

    18 Sep
  • User-friendly system can help developers build more efficient simulations and AI models

    18 Sep
  • 3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities

    18 Sep
  • Expanding robot perception

    18 Sep
  • Toward video generative models of the molecular world

    18 Sep
  • Explained: Generative AI’s environmental impact

    18 Sep
  • Algorithms and AI for a better world

    18 Sep
  • Algorithms and AI for a better world

    18 Sep
  • Making the art world more accessible

    18 Sep
  • Teaching AI to communicate sounds like humans do

    18 Sep
  • Ecologists find computer vision models’ blind spots in retrieving wildlife images

    18 Sep
  • MIT welcomes Frida Polli as its next visiting innovation scholar

    18 Sep
  • MIT researchers introduce Boltz-1, a fully open-source model for predicting biomolecular structures

    18 Sep
  • Study reveals AI chatbots can detect race, but racial bias reduces response empathy

    18 Sep
  • Lara Ozkan named 2025 Marshall Scholar

    18 Sep
  • MIT affiliates named 2024 Schmidt Futures AI2050 Fellows

    18 Sep
  • Teaching a robot its limits, to complete open-ended tasks safely

    18 Sep
  • AI in health should be regulated, but don’t forget about the algorithms, researchers say

    18 Sep

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